Quantification of fiber placement defects in additively manufactured objects embedded with carbon fibers

Additive manufacturing of parts with embedded fibers in planar and spatial patterns has garnered interest due to its potential to enhance their performance. The recent development of spatial steering of fibers in situ with the solidification of the matrix, necessitates the characterization of the morphology of the embedded fibers in a printed part. This work develops methods that leverage image processing to improve the quality of carbon fiber-embedded parts made with vat photo-polymerization. We elucidate the choice and implementation of these metrics that can compare fiber tracks and rank them based on fiber placement characteristics specified by the user. These methods presented here can aid in identifying the ideal machine settings and compare different devices for their performance. Thus, as new devices capable of embedding carbon fiber tracks in additively manufactured parts come up, these metrics serve as a basis for quality optimization and control.